Introduction to Latent Class Analysis
17 June 2020, 9:30 am–5:00 pm
This one day course focuses on understanding the principles of Latent Class Analysis via the concepts and parameters estimated. How to decide on the number of latent classes, and interpretation of the model parameters will be discussed.
Centre for Applied Statistics Courses
There are no dates currently being advertised for this course. More will be advertised shortly to be scheduled from Autumn 2020. In the meantime you can sign up to our mailing list to be the first to find out about any updates:
NOTE: Due to the coronavirus outbreak, all courses will now be delivered online through a live video feed. You can expect the same level of group and individual support as you would have received in our face-to-face courses.
With the advancement of computer simulation, techniques such as Latent Class Analysis are becoming more common in research and can offer a different perspective to certain types of analyses. LCA is a useful approach to identify sub-groups within your data, based on (generally) categorical data. From multiple binary variables for example, using LCA you can reveal common sub-groups in the data that reflect the most frequent patterns, and explore to what extent there is quantitative and qualitative differences within your sample population. While this courses only introduces the concepts of LCA, the information gathered will be useful for those wanting to explore extensions to LCA, such as longitudinal latent models and should attendees want to then start to compute LCA models themselves. This is a theory based course, with no access to software (although some examples are presented with print-screens).
This course covers:
- An introduction to why Latent Class Analysis is used in research
- Explanation of the modelling process, and the parameters estimated
- Details of the model information of how to select the optimum number of latent classes
- LCA model diagnostic criteria
- A real-life example worked through considering the elements listed above
- Brief explanations of extensions to LCA models
- Some provided templates of software use for LCA models
It is expected that you have a decent understanding of probability and basic statistics when attending this course. It would be desirable to have a basic understanding of regression to benefit more from this course, but that isn't essential.
External Delegates (Non-UCL) £150.00 UCL Staff, Students, Alumni £75.00 * Staff and Doctoral Students from ICH/GOSH FREE †
* Valid UCL email address and/or UCL alumni number required upon registration. Please note, this category does not include hospital staff unless you hold an official contract with the university.
† Limited free spaces available. If there are no free places remaining, Staff and Doctoral Students from ICH/GOSH can still register at the UCL rate.
Please note that no refunds will be given for non-attendance or cancellations made within 5 working days of the start of the course. For delegates attending courses on funded places, a £50 fee will be charged for late cancellation, non-attendance or partial-attendance.
- Future dates
^We recommend logging in 10 minutes prior to the scheduled start time to access materials and ensure the course can start promptly at 9.30am.
Dates Times Apply TBC 9.30am - 5.00pm^ Subscribe to general mailing list